PROJECT SUMMARY Breast cancer is the most prevalent cancer in women, and the primary method of detection is screening mammography. Suspicious lesions identified via mammography are further evaluated with secondary imaging modalities and slated for biopsy or surgery based on the severity of suspicion. Mammography has successfully reduced the incidence of mortality due to breast cancer by 20%, but of the 1-2% of mammograms that lead to biopsy, more than 65% are determined to be benign. This indicates that a large majority of biopsies are performed unnecessarily, causing needless physical, emotional, and financial distress for patients. To avoid the occurrence of unnecessary biopsy, the specificity of secondary breast imaging must be improved to accurately and non-invasively differentiate benign from malignant lesions. One of the hallmarks of malignant cancer is angiogenesis, the development of new blood vessels from existing vessels to feed the rapid growth of cancer cells. Tumor-associated angiogenesis leads to very different vascular architecture than that found in healthy tissue, dominated by tortuous, chaotic, leaky vessels. We hypothesize that these microvascular characteristics can be used as a biomarker of malignancy. However, there is a lack of high-resolution, safe, accessible vascular imaging tools in the clinic. Here, we aim to modify and optimize a novel preclinical imaging technique, termed ?acoustic angiography,? for clinical use. Acoustic angiography (AA) is a non-invasive, contrast-enhanced ultrasound imaging technique that produces high-resolution (~150 ?m), three-dimensional microvascular maps. AA requires the use of custom dual-frequency (DF) single-element transducers that severely limit imaging depth (1.5 cm) and suffer from poor sensitivity at clinically-relevant contrast doses. For the clinical translation of AA, DF transducer technology must be improved, and the technique must be optimized at clinical parameters. In this work, we propose to improve the imaging depth and sensitivity of AA by using a novel DF array transducer to implement a clinically-optimized AA imaging scheme. Using in vitro experiments, we will evaluate signal production by ultrasound contrast agents to ensure maximum generation of vascular signatures and optimize acoustic parameters, such as pressure, waveform shape, and filter cutoffs, to maximize contrast-to-tissue ratio. The optimal parameters and type of microbubble that are determined will be validated in vivo in a rat model of fibrosarcoma. We anticipate that this work will facilitate impactful clinical translation of AA in the future.